Resource Management on Distributed Systems: Principles and Techniques - Tapa dura

Acerca del autor

Shikharesh Majumdar is Chancellor’s Professor & Director at Real Time and Distributed Systems Research Centre, Carleton University, Canada. Professor Majumdar earned his PhD in Computational Science from the University of Saskatchewan in 1988 and is a Senior Member of the IEEE and a Fellow of Institute of Engineering and Technology (IET). Professor Majumdar’s research interests include Parallel and Distributed Systems, Operating Systems, Middleware, and many more. He has had many papers published in Journals and Refereed Conference Proceedings, has provided various contributions to many books and is the recipient of multiple awards.

De la contraportada

Complete guide to the principles, algorithms, and techniques underlying resource management for clouds, big data, and sensor-based systems

Resource Management on Parallel and Distributed Systems provides helpful guidance on resource management questions by describing algorithms and techniques for managing resources on parallel and distributed systems, including grids, clouds, and parallel processing-based platforms for big data analytics.

The book introduces four general principles of resource management with a discussion of their impact on system performance, energy usage, and cost, and includes homework question sets at the end of each chapter. To provide complete coverage of the subject, the text includes chapters on sensors, autoscaling on clouds, complex event processing for streaming data, and data filtering techniques for big data systems.

The book also covers results of applying the discussed techniques on simulated as well as real systems (including clouds and big data processing platforms), as well as techniques for handling errors associated with user predicted task execution time.

Written by a highly qualified academic with significant research experience in the field, Resource Management on Parallel and Distributed Systems includes information on sample topics such as:

? Attributes of parallel/distributed applications that have an intimate relationship with system behavior and performance, plus their related performance metrics

? Handling a lack of a prior knowledge of local operating systems on individual nodes in a large system

? Detection and management of complex events (that correspond to the occurrence of multiple raw events) on a platform for streaming analytics

? Techniques for reducing data latency for multiple operator-based queries in an environment processing large textual documents

With comprehensive coverage of core topics in the field, Resource Management on Parallel and Distributed Systems is a complete guide to resource management in a single publication and is an essential read for professionals and researchers working with distributed systems to enable effective resource management within their organizations.